AI in Finance: The Only Practical Guide You Need

It's on the news. It's taking over your LinkedIn feed. You just read a clickbait article on the robo-pocalypse.

AI is here to stay, and it’s swiftly changing how we approach data, business, and decision making.

Have you taken the time to question how to apply AI to aspects of your role as a finance professional? We've got you covered: read on for everything you wanted to know about AI for finance teams.

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What is AI and why is it important to the future of business?

Simply put, AI is the simulation of human intelligence by machines. It involves a wide range of processes, from learning and reasoning, all the way to self-correction.

With AI, we can actually enhance problem solving, planning, and decision making in fields such as robotics, healthcare, and finance. There’s so much buzz around AI because of the incredible potential it has to forever change the way we approach complex problems and find innovative solutions.

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How is AI used in finance, by finance teams?

In general, AI helps finance teams increase the efficiency, accuracy, and speed of financial functions and analysis. Ultimately, AI is a tool — in this case, a powerful tool that supplements the finance team’s role in driving better decisions for the organization.

Here are some specific way finance teams can use AI:

• Analyzing massive quantities of financial data for better informed decisions
• Managing investment portfolios, optimizing trading strategies, and improving risk management
• Detecting and preventing fraud, by flagging potential security breaches and abnormal patterns in data
• Developing more personalized and streamlined processes, by way of automated workflows

In short: it’s everything you were already doing as a finance professional, but faster, more efficiently, and with zero human error.

What finance functions will AI not replace (yet)?

Despite the obvious advantages machines have over humans, AI still needs you, the humble Analyst / Finance Manager / CFO, to set the course. Here are some ideas of what AI cannot effectively do (as of now):

• Relationship management: AI can assist with data analysis and customer interactions, but it can't replace the personal touch of a human being who understands a client or organization’s unique financial needs and goals.
• Strategic decision-making: While you can use AI to eliminate low-impact data processing tasks, your true value as a professional lies in your intuition, prioritization, and strategic thinking.
• Creativity and innovation: This is a tricky one, as we’ve seen especially generative AI be “creative”. However, as convincing as it may be, AI generated outputs and ideas are nowhere as original and out-of-the-box as human creative thinking.
• Regulatory compliance: AI certainly aids financial institutions to detect potential fraud and financial crimes, but it can't replace human oversight when it comes to ensuring compliance with complex regulations and laws.
• Ethical considerations: AI could eventually replace us as decision makers, but we haven’t yet found a way to replicate the human judgment and moral considerations necessary when it comes to sensitive financial decisions — especially since each situation is so unique.

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Examples and unexplored benefits of AI in finance

What’s most exciting is that we’re at the beginning of it all — each day, we discover a new, exciting application for AI. Just check your LinkedIn feed and you’re bound to see the birth of yet another AI startup.

It’s an exciting time, especially if you’re in finance, which has long been a somewhat traditional, slow-to-progress domain. But with the rise of AI, the face of FP&A and other finance functions are transforming faster than before in applications such as:

Generating a summary of reports

Imagine you’re late to your weekly meeting and need to identify your talking points, fast!

One potential benefit of AI is its ability to generate summaries of existing text or charts —  why not ask it to extract call-outs from important financial reports? You’d save time and help your CEO quickly get to the heart of financial information, allowing them to make better decisions.

Automating the budget approval process

An intriguing benefit of AI is its ability to automate routine tasks, such as your budget approval process. This would reduce the workload on finance teams and allow you to focus on high-impact financial activities, while the robots approve (or reject) Marketing’s 19th request for budget adjustments.

Bringing non-finance users up to speed on financial implications

With AI fielding basic questions, you’ll never have to define EBITDA again.

AI could really bridge the gap between business users and finance folks by generating easy-to-understand statements and report summaries, as well as answering FAQs. By providing clear and concise summaries of financial implications, AI can help finance teams be better business partners and improve cross-departmental communication overall.

Finding hidden patterns in your data

Advanced AI algorithms can analyze huge amounts of financial data and detect patterns that may be difficult for human eyes to spot. This would mean that your team can uncover new insights and make better decisions based on the data, not to mention error handling and risk management, as seen below.

Predictive modeling for credit risk management

AI can analyze credit data and payment history to develop models that predict future credit behavior. This can not only help lenders and financial institutions to manage risk, but also enable your firm to offer more targeted and personalized lending options to your customers. As a bonus, you can ask what-if questions to be answered with scenario planning.

Automated fraud detection

AI can ease the pain of fraud prevention by automating the entire process. Since machines do not (yet) have emotions, the technology can objectively monitor transactions in real-time and flag any suspicious activity, helping protect financial institutions and their clients from the damage caused by fraud.

Natural language processing (NLP) for improved customer interactions

Whether you interface with your organization’s customers or internal stakeholders, new-gen AI can field those basic interactions, far better than yesterday’s chatbots — it’s come a long way.

NLP technology will provide a shortcut to understanding and responding to stakeholder inquiries more efficiently. By analyzing customer requests and responses, NLP can provide more personalized and accurate responses, saving time and improving the customer experience.

Tailoring financial products and services

Use AI to better analyze customer data and personalize financial products and services to match their specific needs. This will improve customer satisfaction and ultimately drive revenue growth for financial institutions.

Improved forecasting accuracy

Look, we all love Forecast() but are ashamed to put our names to it. Let AI take over while you get all the glory for spot-on predictions!

One of the best applications of AI in finance is to analyze financial data and make predictions about future trends with greater accuracy than traditional forecasting methods. This can enable your finance team to make more informed decisions about investments, budgeting, and other financial activities.

Enhanced cybersecurity

AI can be used to detect and prevent cybersecurity threats to financial institutions and their clients. By analyzing large amounts of data and identifying patterns of suspicious activity, AI can help to protect financial systems from cyber attacks.

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How AI is fueling the FP&A transformation

If you attended our spectacular FP&A Week event (if not: watch the recordings), you already know that FP&A in particular has been undergoing a rapid transformation. That’s saying something, given that FP&A is a fairly recent development in the finance team structure!

So what’s the change in direction?

Well, FP&A is quickly moving beyond periodic reporting to continuous planning and agile decision-making support. The modern FP&A team is the entire org’s business partner in making better decisions rooted in strategic finance best practices.

Essentially, AI is adding fuel to that fire.

How do you keep up?

Staying up-to-date with the latest advancements in AI can seem overwhelming, especially in the world of finance where things tend to be both more complex and more risky.

But as a finance professional, you win when you keep up with new trends and technologies to stay competitive and effective. Here are some simple and exciting strategies to help you out:

One way to stay in the loop is by attending industry conferences or workshops that focus on AI in finance. These events can teach you a lot and let you meet others who are interested in the same things. It's like going on an adventure and discovering new things along the way.

Another way to learn is by subscribing to industry magazines or websites. They provide valuable information and show you what's happening in the AI-finance world. You can also follow experts on social media. They share their knowledge and help you understand complex ideas in simpler terms.

Remember, you don't have to go on this journey alone. Connect with other finance professionals who are also interested in AI. By talking to them and sharing ideas, you can learn even more. It's like having a map that shows you the best routes to success.

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Challenges slowing down the use of AI in finance

Not everything is perfect — and AI, despite being technology — is no exception. There are several ways applications of AI in finance could backfire:

• Data privacy: One of the biggest challenges of AI is maintaining data privacy and security as more data is collected and analyzed. People have justified concerns about how their data is being used and who has access to it, more so when it’s financial data.
  
  
• Ethical considerations: As AI becomes more advanced, there are concerns about how the technology is being used and its impact on society and individuals. For example, AI's role in automating jobs and decision-making processes raises questions about fairness and bias.
  
  
• Loss of originality: As AI becomes more prevalent, there's a risk of losing the originality and creativity that comes from human input.
  
  
• Creative and critical thinking: As AI automates routine tasks and decision-making, there's a risk of losing the ability to apply critical thinking and creative problem-solving to complex challenges.

How to safeguard the finance team against the drawbacks of AI

First and foremost, understand the limitations of AI. Make sure your team knows what AI can and can't do, so they don't rely on it blindly. It's like knowing the strengths and weaknesses of a teammate. By being aware of its limitations, you can avoid unexpected surprises and inefficient or incorrect use of AI.

Second, human oversight is paramount. AI is a tool, and human judgment is still essential. Your team should have the final say and make critical decisions based on a combination of AI insights and their expertise. Think of it like having an experienced guide alongside you on a challenging hike. Trust your team's expertise and let them exercise their judgment to prevent any potential negative impacts of AI.

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A realistic look at the future of AI in finance

We dreamed of self-driving cars, fully virtual words, and robots taking over menial work for humans. And now, most of those dreams are reality, albeit in an imperfect form.

How will these exciting developments in technology affect finance teams? Regardless of what is to come, finance teams will likely have to invest in change management to move past traditional models towards a faster and more efficient future aided by next-gen tech.

Shameless plug: we’ve announced Pigment AI, to enable business planning that’s as easy as a conversation.

Check out the video below for a quick glimpse of what’s coming to the future of finance, or learn more about Pigment AI.

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